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Informationen zum Autor JAY A. ETCHINGS is the director of operations at Arizona State University's Research Computing program, where he is responsible for developing innovative architectures to progress fluid technical environments supporting highly computational workloads, peta-scale data analysis, next-generation cyber capabilities, and emerging network innovations. Klappentext The ability to apply data science to the biomedical field unlocks the door to boundless innovation and advances in personalized medicine. However, much of the potentially groundbreaking insight big data provides gets lost in translation or goes overlooked due to a lack of transdisciplinary knowledge. Strategies in Biomedical Data Science is the bridge IT professionals need to understand biomedicine, and doctors and researchers need to realize what data and today's advanced technical tools can do for them. This forward-thinking guide for everyone working with biomedical data gives you a way to conceptualize biology, analytics, and IT without having prior training or expertise in any of them. IT and biomedical professionals from the lab to the C-suite will gain a high-level foundation of key concepts in data management and biomedical sciences that enables them to solve real-world human problems and improve patient outcomes. Coverage of cutting-edge applications and technologies throughout the book is reinforced with both case uses demonstrating how they function and case studies looking into how specific organizations use them to overcome challenges. A deep and diverse collection of contributors who practice and study where IT and medicine converge provide a full perspective on the challenges, available solutions, and future potential in the industry. Immediately get a leg up by understanding how to: Efficiently gather data from disparate data sources for effective analysis Get the most out of the latest and preferred analytic resources and technical tool sets Intelligently examine bioinformatics as a service, including the untapped possibilities for medical and personal health devices Data management is the cornerstone of future advances in individualized, patient-specific care, and this complete examination also delves into the operational ways continued advances will evolve medicine, politics, and education, including new professional positions and best practices. Medicine has not had the benefit of big data very long, and Strategies in Biomedical Data Science is your quick and complete jump-start to discover what you have been missing. Zusammenfassung An essential guide to healthcare data problems! sources! and solutions Strategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing deluge of healthcare data. Inhaltsverzeichnis Foreword xi Acknowledgments xv Introduction 1 Who Should Read This Book? 3 What's in This Book? 4 How to Contact Us 6 Chapter 1 Healthcare, History, and Heartbreak 7 Top Issues in Healthcare 9 Data Management 16 Biosimilars, Drug Pricing, and Pharmaceutical Compounding 18 Promising Areas of Innovation 19 Conclusion 25 Notes 25 Chapter 2 Genome Sequencing: Know Thyself, One Base Pair at a Time 27 Content contributed by Sheetal Shetty and Jacob Brill Challenges of Genomic Analysis 29 The Language of Life 30 A Brief History of DNA Sequencing 31 DNA Sequencing and the Human Genome Project 35 Select Tools for Genomic Analysis 38 Conclusion 47 Notes 48 Chapter 3 Data Management 53 Content contributed by Joe Arnold Bits about Data 54 Data Types 56 Data Security and Compliance 59 Data Storage 66 SwiftStack 70 OpenStack Swift Architecture 78 Conclusion 94
